Which integrations are available for this server?

Provides database operations for MySQL including connection management, executing queries, listing tables, and describing table structures. Supports prepared statements for secure query parameter handling.

How do I use MCP MySQL Server?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP MySQL Server show me the 10 most recent orders from the orders table" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

MCP MySQL Server

by Atomzzm

Overview Schema Source Related Servers Discussions Admin

Remote

@f4ww4z/mcp-mysql-server

A Model Context Protocol server that provides MySQL database operations. This server enables AI models to interact with MySQL databases through a standardized interface.

Installation

Installing via Smithery

To install MySQL Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @f4ww4z/mcp-mysql-server --client claude

Manual Installation

npx @f4ww4z/mcp-mysql-server

Related MCP server: MCP MySQL Server

Configuration

The server requires the following environment variables to be set in your MCP settings configuration file:

{
  "mcpServers": {
    "mysql": {
      "command": "npx",
      "args": ["-y", "@f4ww4z/mcp-mysql-server"],
      "env": {
        "MYSQL_HOST": "your_host",
        "MYSQL_USER": "your_user",
        "MYSQL_PASSWORD": "your_password",
        "MYSQL_DATABASE": "your_database"
      }
    }
  }
}

Available Tools

1. connect_db

Establish connection to MySQL database using provided credentials.

use_mcp_tool({
  server_name: "mysql",
  tool_name: "connect_db",
  arguments: {
    host: "localhost",
    user: "your_user",
    password: "your_password",
    database: "your_database"
  }
});

2. query

Execute SELECT queries with optional prepared statement parameters.

use_mcp_tool({
  server_name: "mysql",
  tool_name: "query",
  arguments: {
    sql: "SELECT * FROM users WHERE id = ?",
    params: [1]
  }
});

3. execute

Execute INSERT, UPDATE, or DELETE queries with optional prepared statement parameters.

use_mcp_tool({
  server_name: "mysql",
  tool_name: "execute",
  arguments: {
    sql: "INSERT INTO users (name, email) VALUES (?, ?)",
    params: ["John Doe", "john@example.com"]
  }
});

4. list_tables

List all tables in the connected database.

use_mcp_tool({
  server_name: "mysql",
  tool_name: "list_tables",
  arguments: {}
});

5. describe_table

Get the structure of a specific table.

use_mcp_tool({
  server_name: "mysql",
  tool_name: "describe_table",
  arguments: {
    table: "users"
  }
});

Features

Secure connection handling with automatic cleanup
Prepared statement support for query parameters
Comprehensive error handling and validation
TypeScript support
Automatic connection management

Security

Uses prepared statements to prevent SQL injection
Supports secure password handling through environment variables
Validates queries before execution
Automatically closes connections when done

Error Handling

The server provides detailed error messages for common issues:

Connection failures
Invalid queries
Missing parameters
Database errors

Contributing

Contributions are welcome! Please feel free to submit a Pull Request to https://github.com/f4ww4z/mcp-mysql-server

License

MIT

Available Tools

5 tools

connect_dbC

Connect to MySQL database

ParametersJSON Schema

Name	Required	Description
`host`	Yes	Database host
`user`	Yes	Database user
`password`	Yes	Database password
`database`	Yes	Database name

TDQS

C2.7/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool connects to a database, implying it might establish a session or handle authentication, but it doesn't describe what happens on success or failure, whether connections are persistent, timeouts, or error handling. For a tool with 4 required parameters and no annotations, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste: 'Connect to MySQL database'. It is appropriately sized and front-loaded, clearly stating the core action without unnecessary details. Every word earns its place, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a database connection tool with 4 required parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a connection handle, success status), error conditions, or how it integrates with sibling tools. For a tool that likely enables other operations, more context is needed to guide the agent effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with clear documentation for all 4 parameters (host, user, password, database). The description adds no additional meaning beyond what the schema provides, such as format examples or constraints. Given the high schema coverage, the baseline score of 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Connect to MySQL database' clearly states the verb ('Connect') and resource ('MySQL database'), making the purpose understandable. However, it doesn't distinguish this tool from potential sibling tools like 'describe_table' or 'execute', which might also involve database operations. The purpose is clear but lacks sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., that this must be called before other database tools), exclusions, or context for usage relative to siblings like 'query' or 'list_tables'. Without any usage instructions, the agent must infer when this tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

describe_tableB

Get table structure

ParametersJSON Schema

Name	Required	Description	Default
`table`	Yes	Table name

TDQS

B3.2/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, and the description fails to disclose behavioral traits like read-only nature, side effects, or required permissions. It simply states the function without additional context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise (two words), front-loaded, and gets straight to the point. However, it could benefit from a bit more detail without sacrificing brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool is simple with one parameter and no output schema, the description is minimal but adequate for a basic understanding. However, it doesn't specify what 'structure' includes (e.g., columns, types), leaving some ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with the only parameter 'table' described as 'Table name'. The description adds no new meaning beyond the schema, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get table structure' clearly states the verb (Get) and resource (table structure), and distinguishes the tool from siblings like execute, list_tables, and query, which have different purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool vs alternatives, such as list_tables or query. It lacks context on when not to use it or any prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

executeB

Execute an INSERT, UPDATE, or DELETE query

ParametersJSON Schema

Name	Required	Description	Default
`sql`	Yes	SQL query (INSERT, UPDATE, DELETE)
`params`	No	Query parameters (optional)

TDQS

B3.3/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must bear the burden of behavioral disclosure. It confirms mutation but fails to detail side effects, permanence, or return behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence with no wasted words, but it could include more detail without sacrificing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of output schema and annotations, the description does not explain return values or error behavior. It is too minimal for a mutation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description does not add meaning beyond the schema. The schema already documents 'sql' and 'params' adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool executes INSERT, UPDATE, or DELETE queries, which specifies the action and resource. It distinguishes from sibling tools like 'query' which likely handles SELECT statements.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for write operations but does not explicitly guide when to use this tool versus alternatives like 'query'. There is no mention of prerequisites or restrictions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_tablesB

List all tables in the database

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

B3/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

There are no annotations, so the description must fully disclose behavior. It merely states 'List all tables', which implies a read operation, but omits details on permissions, output format, or performance implications.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with no unnecessary words. It is appropriately front-loaded but lacks any structural enhancement like bullet points that could aid readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema or annotations, the description should explain what 'list' returns (e.g., table names, schemas). Without this, an agent may not know how to use the result. Sibling tools like 'describe_table' suggest additional context might be needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has no parameters, so the description cannot add parameter meaning. Baseline for zero parameters is 4, and the description is sufficient for the parameterless case.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists all tables in the database. While it distinguishes from 'describe_table' by listing instead of describing, it does not explicitly differentiate from potential siblings like 'query' or 'execute'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus its siblings (describe_table, execute, query). It is implied that it retrieves table names, but no context on prerequisites or alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

queryB

Execute a SELECT query

ParametersJSON Schema

Name	Required	Description	Default
`sql`	Yes	SQL SELECT query
`params`	No	Query parameters (optional)

TDQS

B3.1/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description bears full responsibility for behavioral disclosure. It only states the tool executes a SELECT query, but does not explicitly confirm it is read-only, mention permission requirements, error handling, or the effect of malformed queries. The implied read-only nature is not sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence that front-loads the main action. It is not verbose, though it could include more context without losing conciseness. The structure is effective but minimal.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, yet the description does not explain what the tool returns (e.g., result set structure, row count, error messages). It also lacks information on pagination, limits, or behavior with large queries, leaving the agent with significant gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters ('sql' and 'params') adequately. The description adds no additional meaning or context about parameter usage, formatting, or constraints beyond the schema, earning a baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Execute a SELECT query' clearly identifies the tool's action (execute) and resource (SELECT query). It distinguishes from sibling tools like 'execute' (which likely handles other SQL statements) and 'describe_table'/'list_tables' (which are informational).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention that for non-SELECT queries (e.g., INSERT, UPDATE) one should use the sibling 'execute' tool, nor does it specify any prerequisites or limitations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

5 tool updatesJul 31, 2025
- First observedconnect_db
- First observeddescribe_table
- First observedexecute
- First observedlist_tables
- First observedquery

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.4/5.0

Scored 2026-04-18 11:05 across 5 tools

Disambiguation5/5

Each tool has a clearly distinct purpose with no ambiguity: connect_db handles database connections, describe_table retrieves table structures, execute manages data modification queries, list_tables enumerates tables, and query handles SELECT queries. The separation between execute (for INSERT/UPDATE/DELETE) and query (for SELECT) is particularly well-defined.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case: connect_db, describe_table, execute, list_tables, and query. While 'execute' and 'query' are single words, they function as verbs in this context and maintain readability without mixing conventions.

Tool Count5/5

With 5 tools, this server is well-scoped for MySQL database interactions. Each tool earns its place by covering essential operations: connection management, schema inspection, data querying, and data modification. This count is neither too sparse nor bloated for the domain.

Completeness4/5

The tool set provides strong coverage for core MySQL workflows, including connection, schema exploration, and CRUD operations via execute and query. A minor gap exists in lacking explicit tools for database management (e.g., create/drop database) or transaction control, but agents can work around this using execute for such queries.

Maintenance

ActivityInactive

ResponsivenessSyncing

Resources

Need Help?

Reddit Discussion

Related Servers

Related MCP Connectors

hithereiamaliff-mcp-nextcloudOAuth
ai.smithery
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
Cloud Storage File Systems Workplace & Productivity
238
Mercado PagoOAuth
com.mercadopago.mcp
The Mercado Pago MCP Server implements the Model Context Protocol to provide AI agents and LLMs with access to Mercado Pago's APIs and tools within compatible development environments. It acts as an intermediary that translates Mercado Pago resources into executable functions (tools) that AI applications can invoke to perform actions and automate flows. The server simplifies integration, enables using documentation to implement or improve code, and optimizes operations through natural language interactions without manual implementations.
Finance E-commerce & Retail App Automation
2
mcp COAuth
com.wix
A Model Context Protocol server for Wix AI tools
Developer Tools Content Management Systems App Automation
216
dataOAuth
co.thinair
PostgreSQL, MySQL, and SQL Server in one session. 26 read-only MCP tools for AI agents.
Databases Developer Tools
2

Related MCP Servers

MySQL MCP Server
Databases RAG Systems
Mineru98
A
license
Not graded
quality
C
maintenance
A server that enables AI models to interact with MySQL databases through a Model Control Protocol, providing tools for table creation, schema inspection, query execution, and data retrieval.
Updated a year ago (2025-03-23 12:46 UTC)
28
MIT
MCP MySQL Server
Databases Developer Tools
kevinbin
F
license
B
quality
D
maintenance
A Model Context Protocol server that enables AI models to interact with MySQL databases through a standardized interface, providing tools for querying, executing commands, and managing database schemas.
Updated 2 years ago (2025-03-08 03:37 UTC)
7
-
MySQL MCP Server
Databases Search
caicongyang
F
license
Not graded
quality
D
maintenance
A Model Context Protocol server that enables AI models to interact with MySQL databases through natural language, supporting SQL queries, table creation, and schema exploration.
Updated a year ago (2025-06-02 14:57 UTC)
3
-
MySQL MCP Server
Databases Developer Tools Agent Orchestration
michael7736
A
license
A
quality
D
maintenance
A Model Context Protocol server that allows AI agents to execute SQL queries against a MySQL database, supporting operations like reading data, creating tables, inserting, updating, and deleting records.
Updated a year ago (2025-04-10 15:10 UTC)
6
381 npm
7
MIT

@f4ww4z/mcp-mysql-server

Installation

Installing via Smithery

Manual Installation

Configuration

Available Tools

1. connect_db

2. query

3. execute

4. list_tables

5. describe_table

Features

Security

Error Handling

Contributing

License

Available Tools

Tool Schema Changelog

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

Appeared in Searches